dse success factors - research methods term paper

Factors behind the success and sustainability of Dhaka Stock Exchange

An investigation into macroeconomic variables and investor perceptions that affect the

share prices on the Dhaka Stock Exchange

Term paper Research Methodology

Submitted to: Dr. Syed Ferhat Anwar

Professor, IBA. DU Course Coordinator

Submitted by:

Group 1

Omaer Ahmad ZR 09 Kawsar Ahmad ZR 50

Rafaat Waasik Ahmed ZR 53 Nasimul Haque ZR 54

Rashed Al Ahmad Tarique ZR 61

Abstract

Over the last 5 years or so, the Dhaka Stock Exchange has consistently outpaced the

bourses of our neighboring countries and most of the major international exchanges in

terms of return on investment. This paper attempts to identify the relationships between

major macroeconomic factors such as GDP growth, inflation rate, remittances, festivals

and micro factors such as investors’ perception of risk and return on investments in the

DSE relative to other investment opportunities to the DSE General Index. In order to

identify the relationships statistical tools regression, paired t-tests, correlation, and

ARIMA model have been used. ARIMA is used for finding relationship between Pohela

Boishakh and Eid. The stock index is positively correlated with remittance inflow,

however, inflation is negatively correlated. The paper also finds that prime reason that

investors invest in DSE is that they find it enjoying, followed closely by its high return on

investment. In addition, the research finds that investors only relate return from DSE

mildly with return from Real estate. The relationship between Real Estate risk and DSE

risk is also observed to be negatively correlated. There is no significant link between

Pohela Boishakh as an event and DSE Index. In addition, the paper includes analysis of

individual sectors on the stock market and how their stock prices are affected by

occurrence of these factors. We used CAR( Cumulative Abnormal Return) method to

find the variations. The pharmaceuticals stocks were most averse to fluctuations

whereas the banking and insurance industries were the least resilient.

Contents Factors behind the success and sustainability of Dhaka Stock Exchange ....................... 1

Abstract ........................................................................................................................... 2

Introduction ..................................................................................................................... 4

Research objectives ........................................................................................................ 5

Literature review .............................................................................................................. 6

Pre-Qualitative Hypotheses ............................................................................................. 7

Macroeconomic Factor Hypotheses ............................................................................. 7

Primary Qualitative Study ................................................................................................ 8

Post Qualitative hypotheses ............................................................................................ 8

Working definitions ...................................................................................................... 9

Methodology.................................................................................................................. 10

Findings and analysis .................................................................................................... 13

T-test ......................................................................................................................... 14

Frequency Tables and Charts ....................................................................................... 16

Conclusion .................................................................................................................... 24

Annex 1: Questionnaire for investors ............................................................................. 25

Annex 2: List of References .......................................................................................... 28

Introduction

The stock market in Bangladesh, more specifically the Dhaka Stock Exchange (DSE),

has seen a meteoric rise over the last few years. In fact, the DSE General Index has

risen by more than 125% from March 2009 to February 2010. The following figure

provides a comparison of the DSE Index with some major regional and international

markets.

Figure 1: DSE vs. other regional and global indices

As observable from the table, the DSE Index sustained the greatest increase over the

period starting from 2003 to February 2009. Another important observation to be made

from the graph is that the index suffered a significantly milder shock from the global

economic recession. Currently, there are 448 listed companies on the DSE that have a

market capitalization of around Tk. 2,528,317 million. Contrasting this figure with the 267

companies listed in 2003 and a more than tenfold increase in market capitalization, we

can truly gauge the progresses in leaps and bounds of the securities market in

Bangladesh. Recently, the DSE achieved a daily turnover of Tk. 23,057 million. The

number of BO Accounts is approaching 10 million. Therefore, the question that begs to

be asked is what factors contribute to the success of this market.

Figure 2: Important Credit growth statistics, Bangladesh vs. neighbors

Figure 3: Market Turnover Trend, DSE 2003-2010

Despite its remarkable success, market capital is only about 19% of the GDP, which

means a massive potential exists for further listing of firms on the bourse. Therefore,

investigations into the factors that are in fact affecting the DSE, positively or negatively,

need to be performed to ensure the long-term sustainability of this fledgling sector.

In our paper we will be diving into the major macro and micro factors that are relevant to

the success and sustainability of the capital market.

Research objectives The broad objective of our research involves answering the question posed above, i.e.

uncovering the factors that are involved in the success and sustainability of DSE. In

fulfilling our objectives, we must scour through the macroeconomic, microeconomic and

psychographic perceptions of investors. In the first stage, we performed a literature

survey and review that allows us to identify some factors that could give us an answer to

our question.

Literature review

Calendar effect such as holiday and festival affect the stock price. From the study of 17

Muslims countries’ stock market, Jedrzej Bialkowski, Ahmad Etebari, Tomasz Piotr

Wisniewski inferred that returns during Ramadan are almost nine times higher and less

volatile than during the rest of the year. No discernible difference in trading volume is

recorded. They also found that these results consistent with a notion that Ramadan

positively affects investor psychology, as it promotes feelings of solidarity and social

identity among Muslims world-wide, leading to optimistic beliefs that extend to

investment decisions. <Piety and Profits: Stock Market Anomaly during the Muslim Holy

Month>

Investors don’t take the rational decision always, sometimes emotional factor play the

role in stock price. Kathy Yuan, Lu Zheng, Qiaoqiao Zhu, after studying the stock of 48

countries, found that stock returns are lower on days around a full moon than on days

around a new moon. The magnitude of the return difference is 5.4 percent per annum

based on our 15-day window analysis of the global portfolio. The return difference is not

due to changes in stock market volatility. . <Are Investors Moonstruck? Lunar Phases

and Stock Returns>

The returns of Dhaka Stock Exchange do not follow a random walk model and the

significant auto-correlation co-efficient at different lags have found supporting the

hypothesis of weak-form efficiency. Assam Mubarak and Professor Kevin Kasey proved

from their research based on 1988-1997 that Dhaka Stock Market is weak-form efficient.

The results are consistent in different sub-sample observations, without outlier and for

individual securities<Weak-form market efficiency of an emerging Market: Evidence from

Dhaka Stock Market of Bangladesh>

The imposition of the lock-in period has contributed to the price discovery mechanism by

reverting an overall negative risk-return time-varying relationship into a positive one-

sided A. Basher, M. Kabir Hassan, and Anisul M. Islam proved that lock-in did not have

any overall impact on stock volatility; the imposition of a circuit breaker has contributed

significantly to the volatility of realized returns. <Time-Varying Volatility and Equity

Returns in Bangladesh Stock Market>

High volatility, unaccompanied by any change in the real situation, may lead to a general

erosion of investors’ confidence in the market and redirect the flow of capital away from

the stock market. Habibur Rahman, Sakhawat Hossain inferred that there exists

important link between stock market uncertainty and public confidence in the financial

market. The report also suggests that the findings are also applicable for our stock

market. <Volatility of Stock Return in the Dhaka Stock Exchange>

A significant relationship between conditional volatility and the stock returns, but the risk-

return parameter is negative and statistically significant. While this result is not

consistent with the portfolio theory, it is possible theoretically in emerging markets as

investors may not demand higher risk premium if they are better able to bear risk at

times of particular volatility. M. Kabir Hassan, Anisul M. Islam, Side Abu Basher

concludes that While circuit breaker overall did not have any impact on stock volatility,

the imposition of the lock-in period has contributed to the price discovery mechanism by

reverting an overall negative risk-return time-varying relationship into a positive one.

<Market Efficiency, Time-Varying Volatility and Equity Returns in Bangladesh Stock

Market>

Pre-Qualitative Hypotheses

Using scoping, we concentrate on the following macroeconomic factors and investor

perception (to be outlined in the post-qualitative hypothesis segment). The policy

implications on price stability have been subject to many different studies and hence we

can consider those to be law-like generalizations.

Macroeconomic Factor Hypotheses

GDP growth is positively correlated with DSE general index

Inflation is positively correlated with DSE general index

Remittance is positively correlated with DSE general index

“Ekushe Boi Mela” influences DSE general index

“Pohela Boishakh” influences DSE general index

“Eid” influences DSE general index

“Durga Puja” influences DSE general index

Primary Qualitative Study

After the formation of the pre-quali hypotheses from our secondary qualitative research,

we went to Dhaka Stock Exchange to perform our primary qualitative research. We

selected the Key Informant Interview (KII) method for this since only it would provide us

with the necessary information required to formulate our post qualitative hypotheses.

For our interview we selected five investors and three stock brokers as our subject. We selected them on the basis of their extensive experience about Dhaka Stock Exchange.

We asked them about

Their perceptions about the possibility of a crisis in DSE in the near future and how

the current scenario is different from the stock market crash of 1996.

Effects of macro-economic variables such as festivals, political stability, inflation,

natural disaster etc. on DSE performance.

Risks and returns of Dhaka Stock Exchange compared to other investment

opportunities such as, real estate and Bank Fixed Deposit.

Number of investors involved in DSE and their knowledge about the stock market.

Although our interviewees agreed with all of the hypotheses mentioned above, they also

suggested some additional factors behind the recent success of DSE. These factors are

used to formulate our post-qualitative hypotheses about investors which are shown in

the valid hypothesis section below.

Post Qualitative hypotheses

In addition to the above pre-quali hypotheses, we derive the following post-qualitative

hypotheses regarding investors, their perception and habit.

Investor Perception Hypotheses

Investors perceive that investing in DSE will yield higher return than Bank FD

Account.

Investors perceive that investing in DSE will yield higher return than Real Estate.

Investors perceive that investing in DSE is more risky than Real Estate.

Investors invest in DSE because of personal enjoyment.

Investors invest in DSE for high return on investment.

Investors invest in DSE because of habit.

Investors invest in DSE they like to gamble.

Working definitions

Inflation:

Inflation is a rise in the general level of prices of goods and services in an economy over

a period of time. When the price level rises, each unit of currency buys fewer goods and

services; consequently, annual inflation is also erosion in the purchasing power of

money – a loss of real value in the internal medium of exchange and unit of account in

the economy.

In Bangladesh we use the price level of 1996 as a base year and calculate the inflation

on the basis of change in price from that year.

Ekushey Boi Mela:

The duration of ‘Ekushey Boi Mela’ is one month starting from 1st February to 28th

February. We will use the 90 days window that means we will observe the change of

stock price from the 1st January to 31st March.

Pohela Boishakh:

Pohela Boishakh, the first day of the Bengali year, brings the whole nation to a festive

mood. We want to see whether this festiveness affects the stock price. As it occurs on

14th April, we will observe the stock price starting from 14th March to 14th May.

Eid:

Being the Muslim populated (85% of total population) country, Eid-ul-Fitr and Eid-ul-

Azha are the biggest festival in our country. We want to see where this festive mood

affects the stock price. Here we will use the 60 days window.

Methodology

Part of our objective in this research is to identify the emotional and rational aspects in

the investing decision of DSE investors. Investing decision influenced by emotional

factors is reflected in situations marked by rising stock prices during festivals. We plan to

examine the how stock prices of selected industry responds to these events. ’21 e Boi

Mela’, Pohela Boishakh, Eid, Ramadan, and Durga Puja are the events we will be

considering as festivals.

Rational investing decision is reflected in situations where stock prices respond to

events like annual budget announcement. Unlike festivals, investors make rational

investment decisions in such events.

Such effects are similar to interventions in time series data. We intend to measure this

effect in two phases. In the first phase we measure this effect using ‘Cumulative

Abnormal Return’ of industry average stock prices within 15 to 90 days window of the

event. Industry averages are calculated by taking simple average of all the stocks under

the scope within that industry. For missing values in the time series we take the stock

price of the previous day.

Our scoping consists of selecting relatively large industries (i.e. Bank, Financial

Institution, Insurance, Food & Allied, Fuel & Power, Pharmaceuticals, and Textiles) and,

within these industries; companies with regular trading record and that are listed at least

prior to 2006.

In the latter phase we plan to examine using Auto-Regressive Integrated Moving

Average (ARIMA) models whether interventions like such events has any impact on

stock prices.

ARIMA models are widely used in the analysis of time series data and measure effects

of interventions in the time series. ARIMA models are also called Box-Jenkins models.

ARIMA models predict a variable's present values from its past values.

The order of an ARIMA (autoregressive integrated moving-average) model is usually

denoted by the notation ARIMA (p,d,q ), where

p - is the order of the autoregressive part

d - is the order of the differencing

q - is the order of the moving-average process

If no differencing is done (d = 0), the models are usually referred to as ARMA(p, q)

models.

Mathematically the pure ARIMA model is written as

where

t = indexes time

= is the response series or a difference of the response series

= is the mean term

= is the backshift operator; that is,

= is the autoregressive operator, represented as a polynomial in the backshift operator:

is the moving-average operator, represented as a polynomial in the backshift operator:

is the independent disturbance, also called the random error

ARIMA modeling involves three stages: (1) Identification of the initial p, d, and q

parameters, using autocorrelation and partial autocorrelation methods; (2) Estimation of

the p (auto-regressive) and q (moving average) components to see if they contribute

significantly to the model or if one or the other should be dropped; and (3) Diagnosis of

the residuals to see if they are random and normally distributed, indicating a good

model.

Identification of ARIMA parameters:

In this step we need to estimate the best-fit parameter for the Autoregressive component

(p), Integrated component (d), and Moving average component (q).

The values of the p and q parameters may be inferred by looking at autocorrelation and

partial autocorrelation functions as discussed below.

Autocorrelation and partial autocorrelation functions (ACF and PACF) can also be used

to estimate p and q. Specifically, ACF and PACF plots plot deviations from zero

autocorrelation by time period: the larger the positive or negative autocorrelation for a

period, the longer the plot line to the right (positive) or left (negative) of zero.

Autoregressive models. AR models are indicated when PACF cuts off sharply at lag x

but ACF declines slowly. To determine tentatively the value of p, look at the PACF plot

and determine the highest lag at which the PACF is significant.

Moving average models. MA models are indicated by a rapidly declining ACF and PACF.

If the ACF does not decline slowly but rather cuts off sharply at lag x, this is suggests

setting q=x, thereby adding a moving average component. If autocorrelation is negative

at lag-1 then this also indicates the need for an MA (q) term higher than 0.

In SAS, the IDENTIFY statement produces a set of plots namely ACF, IACF, PACF

followed by a White Noise test. White Noise is an approximate statistical test of the

hypothesis that none of the autocorrelations of the series up to a given lag are

significantly different from 0. If this is true for all lags, then there is no information in the

series to model, and no ARIMA model is needed for the series.

Estimation and Diagnostic Checking Stage

Estimation and Diagnostic of the model is done by using ESTIMATE statement in SAS.

ESTIMATE function outputs, among others, "Conditional Least Squares Estimation,"

which indicates the estimation method used, a table of goodness-of-fit statistics which

aid in comparing this model to other models, and a table of correlations of the parameter

estimates which help in assessing the extent to which collinearity might have influenced

the results.

In our research we used a simple ARIMA(1,1) model to see whether these interventions

increased the predicting accuracy of the model by using a dummy input variable

representing the intervention. If the prediction accuracy increases it can be inferred that

the new model is a better fit of the time series data, thus representing a good relation.

In addition to identification of the emotional and rational investing decision of DSE

investors, we plan to examine the impact of remittance and inflation on the performance

DSE general index and selected industry averages.

In order to gain the perception of the demand side, the investors, we have done an

online survey. The sample method used was non-probabilistic, convenient sampling. We

used non-probabilistic sampling because our survey output will be used to identify

factors and not for predicting future outcomes. We prepared a survey form using the

popular GoogleDocs and then posted the link on Facebook and Yahoo Groups pages

which gives platforms to the investors of Dhaka Stock Exchange.

When an investor fills up the questionnaire, GoogleDocs saves all the data in a

spreadsheet and gives us updated information in real time. A sample of the

questionnaire is given in the annexure.

We began our survey by giving the respondents a confidentiality agreement and the

reason for this survey. Then we screened the investors of DSE by asking a dichotomous

question about their investment in the DSE.

For all the three questions in part two, we have used linear regression as the appropriate

analysis technique. We used this to understand the reasons for which people invest in

stock exchange. The options given were: enjoyment, high return on investment,

gambling and habit. Also a blank field was provided to give any alternate reasons for

their investment decision in DSE.

In the third part we requested the respondents to rate the yield of investment from DSE,

Bank FD Account and Real Estate. The rating was done in a six point Likert scale with

very high return and very low return at the two extremities.

Then we compared the risks involved from investing in DSE and real estate. Here also

six point Likert scales were used.

For the analysis part, we did linear regression on the second part of the questionnaire

and for the rest we used paired t-test. The detailed results from analysis of the

questionnaire responses are given in the Findings and Analysis section.

Findings and analysis

A mentioned earlier two types of analysis techniques were used on the data gathered

from questionnaire. For the different reasons why an investor usually invests in the stock

exchange (Question-02), cross tab was done. And for the ratings of risks and returns of

DSE, real estate and Bank Fixed Deposit, paired t-test was done. A total of 52 people

responded to our survey and based on the information they provided us the results are

the following:

T-test

From part three and part four of the questionnaire three pairs were made to performs t-

test. They are return from bank vs. return of DSE, return from real estate vs. return of

DSE, and risk of real estate vs. risk of DSE.

In the table ‘Paired Samples Statistics’, separate summary statistics (mean, N, standard

deviation and standard error) are given for the three pairs.

Paired Samples Statistics

Mean N Std. Deviation Std. Error Mean

Pair 1 Return from bank FD 2.30 53 1.475 .203

DSE 4.64 53 1.442 .198

Pair 2 Real Estate 4.38 53 1.632 .224

DSE 4.64 53 1.442 .198

Pair 3 Real Estate Risk 2.75 53 1.568 .215

DSE Risk 4.77 53 1.325 .182

As we can see that people generally perceive investment in the stock exchange to yield

much higher, almost double, return than bank fixed deposits. In case of return from DSE

this is not the same case. People expect similar returns from both of the investments,

but they perceive a much lower risk associated with real estate.

Paired Samples Correlations

N Correlation Sig.

Pair 1 Return from bank FD & DSE 53 .052 .712

Pair 2 Real Estate & DSE 53 -.105 .455

Pair 3 Real Estate Risk & DSE

Risk

53 -.222 .111

The correlation value in the table ‘Paired Samples Correlations’ indicates the strength of

the variables’ relations. In this table also we see that the effect of bank FD and real

estate have quite opposite effects. People’s perception about bank FD and DSE are

positively correlated while the reverse happens on case of both risk and returns of DSE

and real estate.

From the above tables containing SPSS output from paired t-tests, we can clearly see

that people perceive the Return of DSE to be almost double of Bank FD. They also

perceive the risk from DSE to be twice that of Bank FD. In case of Returns of DSE

versus Returns from Real Estate, they perceive the risk to be much higher in DSE

compared to Real Estate and hence also expect a higher return from DSE compared to

Real Estate. Therefore, all our hypotheses regarding investors’ perceptions about risk

and return are proven.

Bivariate correlation table of Enjoyment, Return on Investment, Habit and Gambling as reasons

behind investment on the Dhaka Stock Exchange

Enjoyment ROI Habit Gambling

Spearman'

s rho

Enjoyment

Correlation

Coefficient 1 .304* .281* 0.168

Sig. (2-tailed) . 0.027 0.042 0.228

N 53 53 53 53

Return on

Investment

Correlation

Coefficient .304* 1 0.038 0.109

Sig. (2-tailed) 0.027 . 0.788 0.436

N 53 53 53 53

Habit

Correlation

Coefficient .281* 0.038 1 .314*

Sig. (2-tailed) 0.042 0.788 . 0.022

N 53 53 53 53

Gambling

Correlation

Coefficient 0.168 0.109 .314* 1

Sig. (2-tailed) 0.228 0.436 0.022 .

N 53 53 53 53

*. Correlation is significant at the 0.05 level (2-tailed).

We have used the Spearman correlation as our sample is non-parametric. From the

table above, there appears to be significant correlation between the factors of

enjoyment, return on investment, habit and gambling. This allows us to validate our

hypothesis regarding the influences which play a part in luring investors to DSE.

Frequency Tables and Charts

Enjoyment

Frequency Percent Valid Percent

Cumulative

Percent

Valid strongly disagree 7 13.2 13.2 13.2

disagree 2 3.8 3.8 17.0

somewhat disagree 5 9.4 9.4 26.4

somewhat agree 7 13.2 13.2 39.6

Agree 5 9.4 9.4 49.1

Highly agree 27 50.9 50.9 100.0

Total 53 100.0 100.0

Return on Investment


Cumulative

Percent

Valid disagree 4 7.5 7.5 7.5



Agree 13 24.5 24.5 66.0

Highly agree 18 34.0 34.0 100.0

Total 53 100.0 100.0

Habit


Cumulative

Percent


disagree 9 17.0 17.0 47.2



Highly agree 11 20.8 20.8 100.0

Total 53 100.0 100.0

Gambling


Cumulative

Percent


disagree 5 9.4 9.4 35.8



Agree 10 18.9 18.9 84.9

Highly agree 8 15.1 15.1 100.0

Total 53 100.0 100.0

From the above frequency tables, it is observed that investors’ rate enjoyment in

investing with the Dhaka Stock Exchange as the greatest influence on them investing on

the DSE followed closely by the higher Return on Investment compared to other

investment alternatives. This further validates our hypotheses regarding the factors that

influence investment decisions in the DSE.

Regression of remittance data with the DSE General Index from April 2008 and May

2010 gives us the following regression line:

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) 7758.258 14259.126 .544 .593

Remittance .057 .063 .297 .894 .384

CPI -36.017 52.461 -.228 -.687 .502

a. Dependent Variable: DSEMonthly

There exists a significant correlation between monthly remittance inflows and DSE

General Index.

The following regression line shows the relationship between DSE General Index and

CPI:

Correlations

DSEMonthly Remittance

DSEMonthly Pearson Correlation 1 .494*

Sig. (2-tailed) .019

N 22 22

Remittance Pearson Correlation .494* 1


N 22 22


The regression line shows an inverse relationship between inflation and the DSE

General Index over the period from April 2010 to May 2008.

Correlations

DSEMonthly CPI

DSEMonthly Pearson Correlation 1 -.458*


N 22 20

CPI Pearson Correlation -.458* 1


N 20 20


From the correlation table we observe that the DSE month-end index values are

inversely correlated with the CPI (Consumer Price Index). Therefore, the hypothesis

regarding a positive correlation between DSE Index and Inflation is disproved.

Correlations

DSEYearEnd

GDPGROWTH

RATE

DSEYearEnd Pearson Correlation 1 -.169


N 6 6

GDPGROWTHRATE Pearson Correlation -.169 1


N 6 6

The correlation table above shows an inverse correlation between the yearend DSE

Index and GDP Growth rate. However there is not a strong correlation. A possible

explanation for this might be that too little information was taken to actually get the real

correlation effect. So the hypothesis regarding relation between DSE Index and GDP

Growth rate is disproved.

The following table uses the cumulative abnormal return (CAR) method to find the

changes that are experienced by sectors as a result of festivals and events popular in

Bangladesh. This is calculated by the difference between the average returns of the

sector in comparison with the average return of the stock exchange over a given period

of time. The times are specified for each event in the working definitions section. The

data is calculated from 2006 to 2009.

EVENTS YEAR DSE Gen INSURANCE FOOD PHARMA BANK

Boi mela 2006 -0.16859 0.152374 0.165982 -0.0823 -0.17886

Boi mela 2007 -0.06025 0.038248 0.082066 0.017092 -0.07706

Boi mela 2008 0.001274 0.29104 0.273986 0.020714 0.004707

Boi mela 2009 0.052119 0.08897 0.033468 0.012153 -0.17835

Pohela pre 2006 -0.00519 -0.04231 -0.10908 -0.04495 -0.18075

Pohela pre 2007 -0.02051 -0.02051 -0.08358 -0.11466 -0.10222

Pohela pre 2008 -0.01156 0.226153 0.030724 0.061495 -0.13929

Pohela pre 2009 0.00896 -0.19748 0.116264 -0.04335 -0.34508

Pohela post 2006 0.034059 -0.01894 -0.01003 -0.03304 -0.36062

Pohela post 2007 0.0788 -0.08858 -0.04866 -0.13155 -0.36827

Pohela post 2008 -0.00264 -0.12961 -0.00268 0.022966 -0.17673

Pohela post 2009 -0.02108 -0.00848 -0.11716 -0.0197 -0.12566

Pre eid roja 2006 -0.03384 -0.01111 0.083309 0.029024 -0.27896

Pre eid roja 2007 0.084911 -0.06852 0.000304 0.018075 -0.09397

Pre eid roja 2008 0.016355 0.017854 0.038559 0.135259 -0.05407

Pre eid roja 2009 -0.17394 -0.17394 0.291543 0.045298 -0.17551

Post eid roja 2006 0.037409 -0.12363 -0.15062 -0.0655 -0.08849

Post eid roja 2007 0.036364 0.324516 -0.08776 -0.01398 0.043369

Post eid roja 2008 -0.10655 0.094815 0.092389 0.134479 -0.04673

Post eid roja 2009 0.046555 -0.08419 0.078978 0.010517

Puja 2006 -0.03679 -0.05339 -0.51392

Puja 2007 -0.00079 0.074951 0.028279

Puja 2008 -0.07613 0.017143 0.146644 0.233822 -0.11564

Puja 2009 0.133571 0.065976 -0.232 -0.11606 0.051128

Pre eid kurb 2006 -0.03003 -0.03003

Pre eid kurb 2007 0.028923 -0.08833 -0.05592 -0.09069 0.00501

Pre eid kurb 2008 0.090793 -0.21406 -0.04113 -0.08395 -0.09031

Pre eid kurb 2009 0.072161 0.125582 -0.11999 -0.21087 0.080134

Post eid kurb

2007 0.11221 -0.03778 0.056158 -0.0754 0.046415

Post eid kurb

2008 -0.02662 0.163842 0.141872 -0.03571 -0.14719

Post eid kurb

2009 -0.03768 0.233487 0.085306 -0.06347

Post eid kurb

2009 0.061411 -0.20179 -0.04338 -0.02901

From the table, it is observed that there is not a significant impact of the events and

festivals on the DSE Index overall. However, different industries are seen to react

differently to different events. As observed from the data, the insurance and banking

industries appear to be most reactive to these events. On the other hand, the

pharmaceuticals industry appears to be the most stable to the changes in local festivities

and events.

Conclusion

The paper took inspiration from a number of interesting and thought-provoking writings

of experts around the world and attempted to indentify the alignment of international

trends in our local context. It used statistical techniques such as paired t-tests, Pearson

and Spearman correlations, simple linear regressions and ARIMA predictive models. We

also observed how national festivals and events affect the share prices of some industry

stocks. We used CAR ( Cumulative Abnormal Return) method to find the variations. The

pharmaceuticals stocks were most averse to fluctuations whereas the banking and

insurance industries were the least resilient. The paper also finds that prime reason that

investors invest in DSE is that they find it enjoying, followed closely by its high return on

investment. In addition, the research finds that investors only relate return from DSE

mildly with return from Real estate. The relationship between Real Estate risk and DSE

risk is also observed to be negatively correlated. Finally it paves the way for further

research to be carried out on the factors outside the scope of this paper.

Annex 1: Questionnaire for investors

DSE Investor perception of risk in and return on Investment

We are a group of students from IBA conducting a study on the factors that lead to the

success and sustainability of Dhaka Stock Exchange (DSE). To understand these

factors, we are seeking information from the viewpoint of the investors of the DSE on the

risks and returns of investments in the DSE. All the data collected from respondents will

be kept confidential and will only be used for the purposes of this course. If you are an

investor in DSE, we will highly appreciate your help in filling out the following

questionnaire.

* Required Have you invested in Dhaka Stock Exchange (DSE) within the last 12 months? *

Yes

No

The following section contains some questions based on your reasons

for investing in the DSE

Please rate this by degree of your preference. Consider 6=Most important and 1=Least

important

Did you invest in DSE because you find it enjoying? *

1 2 3 4 5 6

Do you invest in DSE because you find its return on investment high? *

1 2 3 4 5 6

Do you invest in DSE because of habit? *

1 2 3 4 5 6

Do you invest in DSE because of the excitement from gambling with stocks? *

1 2 3 4 5 6

If others, please specify

The following section contains some questions regarding your preference for different investment opportunities Please rate each of the following investments according to return. 6=Very high return and 1=Very low return Bank Fixed Deposit Account *

1 2 3 4 5 6

Real Estate *

1 2 3 4 5 6

Dhaka Stock Exchange *

1 2 3 4 5 6

The following section contains some questions about your perception of risk in different investments Please rate each of the following investment opportunities in terms of risk 6=Very high risk and 1= very low risk Real Estate *

1 2 3 4 5 6

Dhaka Stock Exchange *

1 2 3 4 5 6

4. Please feel free to give any additional comments

Submit

Powered by Google DocsReport Abuse - Terms of Service - Additional Terms

http://docs.google.com/



http://www.google.com/accounts/TOS

http://www.google.com/google-d-s/terms.html

Annex 2: List of References

Piety and Profits: Stock Market Anomaly during the Muslim Holy Month - Jedrzej Bialkowski, Ahmad Etebari, Tomasz Piotr Wisniewski Are Investors Moonstruck? Lunar Phases and Stock Returns - Kathy Yuan, Lu Zheng, Qiaoqiao Zhu Weak-form market efficiency of an emerging Market: Evidence from Dhaka Stock Market of Bangladesh - Assam Mobarek and Professor Keavin Keasey Time-Varying Volatility and Equity Returns in Bangladesh Stock Market - Syed A. Basher, M. Kabir Hassan, and Anisul M. Islam Volatility of Stock Return in the Dhaka Stock Exchange - Habibur Rahman, Sakhawat Hossain Market Efficiency, Time-Varying Volatility and Equity Returns in Bangladesh Stock Market - M. Kabir Hassan, Anisul M. Islam, Syed Abul Basher www.dsebd.org www.bangladesh-bank.org www.bbs.gov.bd www.thedailystar.net AT Capital Research - Bangladesh - Growth, Investment, Opportunity www.theindependent-bd.com

Bangladesh Economic Online

http://www.dsebd.org/

http://www.bangladesh-bank.org/

http://www.bbs.gov.bd/

http://www.thedailystar.net/

http://www.theindependent-bd.com/

dse success factors - research methods term paper

Documents